Fixture plays an important part in constraining excessive sheet metal part deformation at machining, assembly, and measuring\nstages during the whole manufacturing process. However, it is still a difficult and nontrivial task to design and optimize sheet metal\nfixture locating layout at present because there is always no direct and explicit expression describing sheet metal fixture locating\nlayout and responding deformation. To that end, an RBF neural network prediction model is proposed in this paper to assist design\nand optimization of sheet metal fixture locating layout. The RBF neural network model is constructed by training data set selected\nby uniform sampling and finite element simulation analysis. Finally, a case study is conducted to verify the proposed method.
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